Data type definition and handling for supporting interoperability across organizational borders

Dávid Karnok, Zsolt Kemény, Elisabeth Ilie-Zudor, L. Monostori

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Organisational heterogeneity—especially in networks where new members may join at any time—requires ongoing actions to maintain interoperability. On the level of data interoperability, this highlights the importance of various aspects of data model and dataflow design, as well as handling of data at run-time. The latter is certain to require automated means of data model negotiation, and—while today’s design processes are far from fully automated—such means can leverage productivity and support verification procedures in data modelling and dataflow design as well. The paper presents results in one possible approach to data type definition and manipulation, through the example of the ADVANCE dataflow engine and its type-related features. Aside from an XML-based type system, type inference algorithms are presented which are employed both during design and flow execution.

Original languageEnglish
Pages (from-to)167-185
Number of pages19
JournalJournal of Intelligent Manufacturing
Volume27
Issue number1
DOIs
Publication statusPublished - Feb 24 2014

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Keywords

  • Dataflow
  • Enterprise network
  • Type inference
  • XML type system

ASJC Scopus subject areas

  • Software
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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